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Alt-Ergo is an automatic theorem prover dedicated to program verification. Alt-Ergo is based on CC(X), a congruence closure algorithm parameterized by an equational theory X. Currently, CC(X) can be instantiated by the empty equational theory and by the linear arithmetics. Alt-Ergo contains also a home made SAT-solver and an instantiation mechanism. Alt-Ergo is compact, safe, and modular. Each component is described by a small set of inference rules and is implemented as an Ocaml functor.

Minpack includes software for solving nonlinear equations and nonlinear least squares problems. Five algorithmic paths each include a core subroutine and an easy-to-use driver. The algorithms proceed either from an analytic specification of the Jacobian matrix or directly from the problem functions. The paths include facilities for systems of equations with a banded Jacobian matrix, for least squares problems with a large amount of data, and for checking the consistency of the Jacobian matrix with the functions

JAGS is Just Another Gibbs Sampler -- a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation. The functionality of JAGS is based on the BUGS program created by the MRC Biostatistics Unit (http://www.mrc-bsu.cam.ac.uk/). There is a short manual that describes the differences between JAGS and BUGS. Some of the BUGS examples have been modified to run with JAGS, and have been turned into a test suite.

The octave-forge package is the result of The GNU Octave Repositry project, which is intended to be a central location for custom scripts, functions and extensions for GNU Octave. contains the source for all the functions plus build and install scripts. This is bim. Package for solving Diffusion Advection Reaction (DAR) Partial Differential Equaltions based on the Finite Volume Scharfetter-Gummel (FVSG) method a.k.a Box Integration Method (BIM)

This module was adapted from Math::Vector. It uses most of the same algorithms, and currently preserves the same names as the original functions, though some aliases have been added to make the interface more natural. The "object" for the object oriented calling style is a blessed array reference which contains a vector of the form [x,y,z]. Methods will typically return a list.

The Math::VectorReal package defines a 3D mathematical "vector", in a way that is compatible with the previous CPAN module Math::MatrixReal. However it provides a more vector oriented set of mathematical functions and overload operators, to the MatrixReal package. For example the normal perl string functions "x" and "." have been overloaded to allow vector cross and dot product operations. Vector math formula thus looks like vector math formula in perl programs using this package.

Proof General is a generic interface for proof assistants, currently based on the customizable text editor Emacs. It works with either XEmacs or GNU Emacs. A new Eclipse-based version is in development. This is described separately at http://proofgeneral.inf.ed.ac.uk/kit/wiki. Proof General has been developed at the LFCS in the University of Edinburgh. It is distributed under the conditions of the GNU General Public License. There is a mailing list: http://proofgeneral.inf.ed.ac.uk/mailinglist

Graphillion is a Python software package on search, optimization, and enumeration for a graphset, or a set of graphs. - Lightweight data structures for handling x-illions of graphs - Search, optimization, and enumerate large and complex graph sets - Efficient implementation extending Python with C/C++ - Working with existing graph tools like NetworkX - Open source MIT license - Well tested: more than 600 unit tests - Fast prototyping, easy to teach, and multi-platform

Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC), is an increasingly relevant approach to statistical estimation. However, few statistical software packages implement MCMC samplers, and they are non-trivial to code by hand. pymc is a python package that implements the Metropolis-Hastings algorithm as a python class, and is extremely flexible and applicable to a large suite of problems. pymc includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics.

This port contains data and baseline images for VTK regression testing and other VTK examples. The Data directory are data files of various types. This includes polygonal data, images, volumes, structured grids, rectilinear grids, and multi-variate data. The Baseline are the testing images. These are used in testing to compare a valid image against a generated image. If a difference between the two images is found, then the test is considered to have failed.